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RUST ENGINE / solve_equilibrium

Kuhn poker equilibrium with CFR+

Explore a small imperfect-information game with a Rust self-play solver and compare its result with a known equilibrium value.

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How it works

The solver applies regret-based self-play to two-player Kuhn poker. It reports decision probabilities, game value and exploitability rather than interpreting the behaviour of real players.

Inputs and units

Choose a bounded iteration count. The demonstration uses 200,000 iterations; increasing the count explores convergence for this particular toy game.

What the result contains

A strategy table, estimated game value and exploitability make the computation inspectable. The analytical reference game value is −1/18 for the first player.

Example MCP call

{
  "name": "solve_equilibrium",
  "arguments": {
    "iterations": 200000
  }
}

Send this tool name and arguments through a connected MCP client. Discover the authoritative input schema with tools/list.

Execution and availability

ScoreCompute exposes this tool through MCP Streamable HTTP. Rust computation runs on a connected worker; the public website and MCP gateway run separately. CUDA is implemented for simulate_pi; the other tools currently run on CPU. Requests are bounded and concurrent work may be refused when capacity is occupied.

Record inputs, assumptions and returned provenance when sharing a result. The public observatory displays software client names and tool activity, without publishing calculation arguments or results.

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